Triple

T21584700
Position Surface form Disambiguated ID Type / Status
Subject N Seoul Tower E532617 entity
Predicate alsoKnownAs P39 FINISHED
Object Namsan Seoul Tower NE NERFINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Namsan Seoul Tower | Statement: [N Seoul Tower, alsoKnownAs, Namsan Seoul Tower]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Namsan Seoul Tower
Context triple: [N Seoul Tower, alsoKnownAs, Namsan Seoul Tower]
  • A. N Seoul Tower chosen
    N Seoul Tower is a prominent communication and observation tower on Namsan Mountain that serves as one of Seoul’s most recognizable cityscape landmarks and tourist attractions.
  • B. Mount Namsan
    Mount Namsan is a historically significant mountain in Gyeongju, South Korea, renowned for its numerous ancient Buddhist relics, temples, and archaeological sites.
  • C. Kyobo Tower, Seoul
    Kyobo Tower in Seoul is a prominent modern office and commercial building best known as a landmark work of Swiss architect Mario Botta.
  • D. Busan Tower
    Busan Tower is a prominent observation tower in Busan, South Korea, offering panoramic views of the city and its harbor.
  • E. Trade Tower (Seoul)
    Trade Tower (Seoul) is a prominent skyscraper and major business complex in Seoul’s Gangnam district, known for housing offices, exhibition spaces, and being part of the COEX convention and shopping area.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69e0c4618bec8190bcb0feb74568cbb1 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69eeeb5f2cc0819095552de70eb2ad8d completed April 27, 2026, 4:51 a.m.
Created at: April 16, 2026, 6:31 p.m.